Analysis of whole blood using flow cytometry

Abstract

The present disclosure relates to systems and methods for analyzing particles within a flow cytometry system. A method for analyzing particles within a whole blood sample includes receiving a whole blood sample. Furthermore, the method includes receiving a panel selection relating to one or more constituents within the whole blood sample, wherein the one or more constituents include one or more desired constituents. Furthermore, the method includes adding at least one labeling reagent to the whole blood sample, wherein the at least one labeling reagent is configured to label the one or more desired constituents. Further yet, the method includes collecting flow cytometry data from the whole blood sample and analyzing the one or more constituents.

Description

ANALYSIS OF WHOLE BLOOD USING FLOW CYTOMETRYCROSS REFERENCE TO RELATED APPLICATION

[0001] This application is being filed as a PCT International patent application and claims priority’ to and the benefit of U.S. Provisional Patent Application Number 63 / 585,449 filed on September 26, 2023, the subject matter of which is hereby incorporated by reference in its entirety.BACKGROUND

[0002] Flow cytometry is a technique for detecting and analyzing chemical and physical characteristics of cells or particles in a fluid sample. For example, a flow cytometer may be used to assess cells from blood, bone marrow, tumors, or other body fluids. Typically, the sample is passed through a fluid nozzle which aligns particles in a single file line within a sheath fluid. A laser beam illuminates the particles as they pass through in single file to generate radiated light including forward scattered light, side scattered light, and fluorescent light. The radiated light can then be detected and analyzed to determine one or more characteristics of the particles, including the particle’s size, shape, granularity, and fluorescent properties.

[0003] In certain examples, it is desirable to isolate a specific subset of particles for analysis. In biological applications that include whole blood samples, this can be completed by lysing unwanted cells and washing the sample to leave behind a desired cell population, and flow cytometry data can be generated from the lysed / washed sample. However, lysing, washing, and other sample manipulation steps may negatively impact the integrity of a desired subset of cells before they are analyzed. Thus, it is desirable to isolate a desired subset of cells for further analysis while preserving the integrity of the desired subset of cells that are being analyzed.SUMMARY

[0004] In general terms, the present disclosure relates to analyzing cells found in whole blood (e.g., white blood cells, red blood cells, blood platelets, etc.) using flow cytometry. Specifically, the present disclosure relates to isolating cell types within a whole blood sample. In one possible configuration, flow cytometry data is collected from a whole blood sample that was not prepared using any lysing, washing, or dilution steps.In another possible configuration, the whole blood sample is analyzed by considering various waveforms (e.g., forward scatter data, side scatter data, or fluorescence data relating to the intensity of a fluorochrome-labeled antibody) including events that are detected by the flow cytometer. In another possible configuration, events are detected by the flow cytometer without aborting any events (i.e., zero events are discarded during a data acquisition phase due to reasons such as cellular clumping at the interrogation zone, the presence of contaminants, signal noise, etc.). Various aspects are described in this disclosure, which include, but are not limited to, the following aspects.

[0005] One aspect relates to a method for analyzing particles within a flow cytometry system. The method includes receiving a whole blood sample. Furthermore, the method includes receiving a panel selection relating to one or more constituents within the whole blood sample. Furthermore, the method includes adding at least one labeling reagent to the whole blood sample, wherein the at least one labeling reagent is configured to label the one or more desired constituents. Further yet, the method further includes collecting flow cytometry data from the whole blood sample and analyzing the one or more constituents.

[0006] Another aspect relates to a method for analyzing flow cytometry data. The method includes receiving flow cytometry data, wherein the flow cytometry' data includes one or more dimensions to quantify characteristics of whole blood constituents within a whole blood sample, and wherein the whole blood constituents include at least one constituent of interest and at least one other constituent. Furthermore, the method further includes identifying the at least one constituent of interest. Furthermore, the method includes isolating at least one event pertaining to the at least one constituent of interest by identifying when the flow cytometry data indicates at least one event includes the characteristics that pertain to the at least one constituent of interest. Further yet, the method includes analyzing the at least one constituent of interest independently from the at least one other constituent.

[0007] Y et another aspect relates to a flow cytometry system for analyzing particles.The flow cytometry system includes at least one processing device. Furthermore, the flow cytometry system includes a non-transitory computer readable storage media storing instructions which, when executed by the processing device, cause the at least one processing device to receive flow cytometry data, wherein the flow cytometry' data includes one or more dimensions to quantify characteristics of whole blood constituents within a whole blood sample, wherein the whole blood constituents include at least oneconstituent of interest and at least one other constituent. Furthermore, the flow cytometry system includes a non-transitory computer readable storage media storing instructions which, when executed by the processing device, cause the at least one processing device to identify the at least one constituent of interest. Furthermore, the flow cytometry system includes a non-transitory' computer readable storage media storing instructions which, when executed by the processing device, cause the at least one processing device to isolate at least one event pertaining to the at least one constituent of interest by identifying when the flow cytometry data indicates at least one event includes the characteristics that pertain to the at least one constituent of interest. Further yet, the flow cytometry system includes a non-transitory computer readable storage media storing instructions which, when executed by the processing device, cause the at least one processing device to analyze the at least one constituent of interest independently from the at least one other constituent.

[0008] A variety of additional aspects will be set forth in the description that follows. The aspects can relate to individual features and to combinations of features. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the broad inventive concepts upon which the examples disclosed herein are based.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The following drawings are illustrative of examples of the present disclosure and therefore do not limit the scope of the present disclosure. Examples of the present disclosure will hereinafter be described in conjunction with the appended drawings, wherein like numerals denote like elements.

[0010] FIG. 1 depicts an example sample preparation instrument.

[0011] FIG. 2 is a block diagram of the example sample preparation instrument.

[0012] FIG. 3 is a block diagram of basic hardware components of the example sample preparation instrument.

[0013] FIG. 4 schematically illustrates an example of a flow cytometer system for analyzing samples prepared by the sample preparation instrument.

[0014] FIG. 5 schematically illustrates an example of a waveform analysis device of the flow cytometer system of FIG. 4.

[0015] FIG. 6 illustrates a method of preparing a sample for analysis that includes lysing and washing the sample.

[0016] FIG. 7 illustrates a method of preparing a sample for analysis that does not include manipulating the sample by lysing, washing, or diluting the sample.

[0017] FIG. 8 illustrates a method of analyzing a whole blood sample using the waveform analysis device of FIGS. 4-5.

[0018] FIG. 9 illustrates sample waveforms generated by the flow cytometry system of FIG. 4, including events that generated a forward scatter, a side scatter, and / or a fluorescence of a fluorochrome-labeled antibody.

[0019] FIG. 10 illustrates a sample event that is indicative of a white blood cell.

[0020] FIG. 11 illustrates example graphs that show the desired constituents being isolated from the other constituents within a whole blood sample.

[0021] FIG. 12 illustrates an example method of analyzing flow cytometry data that was collected without aborting any events during the collection phase.

[0022] FIG. 13 illustrates an exemplar}' architecture of a computing device that can be used to implement aspects of the present disclosure.

[0023] In the appended figures, similar components and / or features can have the same reference label. Further, various components of the same type can be distinguished by following the reference label by a dash and a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.DETAILED DESCRIPTION

[0024] Various examples will be described in detail with reference to the drawings, wherein like reference numerals represent like parts and assemblies throughout the several views.

[0025] FIG. 1 depicts an example sample preparation instrument 100. The sample preparation instrument 100 can be used to prepare a sample of a specimen for subsequent analysis, such as for a flow cytometry panel. Example specimens can include whole blood, bone marrow, dissociated tissues, peripheral mononuclear cells, fine needle aspirates, cerebrospinal fluid, and other single cell-suspensions. As one example, a laboratory providing flow cytometry services receives a whole blood specimen to be prepared for a leukemia or lymphoma panel. Constituents of blood include plasma, red blood cells, white blood cells, and platelets. Leukemia or lymphoma affects white blood cells (e.g., cause abnormally high white blood cell counts), and therefore subsets of thewhite blood cells are the constituent of the blood that is targeted for analysis in the leukemia or lymphoma panel.

[0026] To prepare a sample of the blood for the panel, a labeling reagent, such as an antibody reagent that attaches to white blood cells, is used to stain the blood. For example, about 100 pL of blood is stained with about 20 pL of the antibody reagent and incubated for about 10 to 20 minutes. The antibody reagent can include a fluorescent dye, for example, which allows for analysis of the white blood cells by flow cytometry. In some examples, cell washing is performed on the blood prior to adding the antibody reagent in order to remove the plasma and associated proteins that interfere with staining (e.g., such that primarily red blood cells and white blood cells remain).

[0027] In some instances, the sample preparation instrument 100 can include aspects and features described in U.S. Provisional Patent Application No. 62 / 954299, filed December 27, 2019, and U.S. Non-provisional Patent Application No. 17 / 127439, filed on December 18, 2020, which are both herein incorporated by reference in their entireties.

[0028] Currently, to analyze white blood cells using a flow cytometer, a lytic reagent is added to the sample and incubated to destroy the red blood cells and increase a ratio of white blood cells to red blood cells. In a standard whole blood sample, red blood cells greatly outnumber white blood cells (sometimes by a ratio of approximately one thousand to one). Thus, it is difficult to isolate white blood cells within a whole blood sample due to the high ratio of red blood cells to white blood cells.

[0029] In some examples, after adding the lytic agent, a wash can be performed to slow the lytic activity' to avoid destruction of the white blood cells and / or to remove red blood cell debris prior to analyzing the sample. However, washing the sample does not guarantee the white blood cells will be suitable for analysis, as the lytic agent may affect the integrity of the white blood cells and negatively impact the results of any experiment used to analyze white blood cells within a whole blood sample.

[0030] Current whole blood sample preparation methods often include a step to dilute the whole blood sample (i.e.. add a diluent such as a buffer solution). It may be desirable to dilute a whole blood sample to reduce the abort rate in that sample, which is the rate at which events are discarded for various reasons (e.g., clumping of red blood cells) during a data collection phase when the sample is analyzed with a flow cytometer. Diluting a sample minimizes the clumping of cells and lowers the abort rate; however, this can lower the concentration of white blood cells within a whole blood solution tolevels that are not suitable for analysis. The abort rate is illustrated and described in further detail with respect to FIG. 12.

[0031] Aspects of this disclosure provide a more streamlined sample preparation process to overcome the above-discussed disadvantages of current systems and methods. For example, the sample preparation instrument 100 described in detail in the following figures includes a sample preparation instrument 100 that prepares whole blood samples for analysis within a flow cytometer system 300. The sample preparation instrument 100 prepares the samples without adding a lytic agent or diluting the whole blood sample. Thus, in one example, the whole blood sample is a sample in which no lysing or washing steps have occurred. In this example, the white blood cells within the whole blood sample are not damaged by a lysing step, and they remain suitable for analysis. This process is described in further detail with respect to FIGS. 6-10.

[0032] Furthermore, the flow cytometer system 300 includes a waveform analysis device 150 having a whole blood cell identifier 354 that differentiates cells within a whole blood sample by analyzing waveforms that are created during data collection steps using the flow cytometer system 300. The flow cytometer system 300 is configured to collect data at pertaining to a whole blood sample without aborting any events during the data collection phase, which is discussed below in further detail with respect to FIGS. 11-12. Collecting data without aborting any events is desirable because it limits the amount of data that is erased during a collection stage when the flow cytometer system 300 is unable to recognize an event. In certain examples, a non-zero number of events can be aborted by the flow7cytometry system 300.

[0033] FIG. 2 is a block diagram of the example sample preparation instrument 100. The sample preparation instrument 100 receives a specimen, of which a sample is to be prepared for analysis, as input 102. In some examples, the analysis targets specific constituents of the specimen, such as a red blood cell or a white blood cell. The sample preparation instrument 100 can estimate a concentration of the targeted constituents in the specimen and prepare a sample accordingly to provide a prepared sample as output 104. For example, a sample volume of the specimen can be determined based on the estimated concentration and a set of predefined rules associated with a type of the analysis the specimen is being prepared for. Reagents can be added to the sample volume of the specimen, where the reagents can include labeling reagents to target a desired constituent of the specimen for analysis.

[0034] FIG. 3 is a block diagram of basic hardware components of the example sample preparation instrument 100. The sample preparation instrument 100 includes at least a cell concentration estimator 106, a reagent station 108, and a reaction station 109.

[0035] The sample preparation instrument 100 receives the specimen to be prepared for analysis as the input 102. As one example, the specimen is whole blood to be prepared for a leukemia or lymphoma panel performed by a flow cytometer. The leukemia or lymphoma panel can be performed to analyze subsets of white blood cells in the blood (e g., the subsets of the white blood cells can be the targeted constituents). The cell concentration estimator 106 is a device or apparatus that can receive an aliquot of the specimen and estimate a white blood cell concentration in the specimen based on an estimated white blood cell concentration in the aliquot. The cell concentration estimator 106 can employ one or more of an optical method, an electrical resistance method, a flow cytometry method, and other similar methods known to one of ordinary' skill in the art for estimating white blood cell concentration. A configuration of the cell concentration estimator 106 can be dependent on a type of method employed. Based on the estimated white blood cell concentration in the specimen, a sample volume of the specimen (e.g.. a volume of the specimen to be included in the sample prepared for analysis) is determined.

[0036] The reagent station 108 can include a plurality of labeling reagents, where one or more of the labeling reagents are added to the determined sample volume of the specimen. The one or more labeling reagents added can target particular constituents within the sample volume of the specimen. For example, continuing the above example, the reagents can be antibody reagents having fluorescent dyes that attach to the subsets of white blood cells to allow for analysis of the subsets of white blood cells by the flow cytometer when performing the leukemia or lymphoma panel. In certain examples, the labeling reagents include fluorochrome-labeled antibodies. In certain examples, fluorochromes used to label specific antibodies include fluorescein isothiocyanate (FITC), and the specific antibodies include CD4, CD8, CD 19, CD45, or other antibodies commonly used to target cells found in whole blood.

[0037] In some examples, the labeling reagents and the sample volume of the specimen come into contact at the reaction station 109. For example, the labeling reagents can be added to the sample volume of the specimen within a w ell of a reaction plate located within the reaction station 109. The reaction station 109 can also include a plate mixer that holds the reaction plate. In some examples, the reaction station 109 is aseparate component of the sample preparation instrument 100. In other examples, the reaction station 109 can be integrated with the reagent station 108.

[0038] Following addition of the labeling reagents, a sample comprising the sample volume of the specimen with the added labeling reagents is provided as the output 104 of the sample preparation instrument 100. The sample can then be analyzed by a sample analyzer, such as a flow cytometer. In some examples, the sample analyzer is a separate component. In other examples, the sample analyzer can be integrated with the sample preparation instrument 100.

[0039] FIG. 4 schematically illustrates an example of a flow cytometer system 300. In some instances, the flow7cytometer system 300 can include aspects and features described in U.S. Provisional Patent Application No. 63 / 410,984. filed September 28, 2022, and in PCT Application No. PCT / US2023 / 033685, filed on September 26, 2023, published as WO2024 / 072782, which are hereby incorporated by reference in their entireties.

[0040] In general, flow cytometry is a technique for measuring and analyzing properties of particles or cells when flowing in a fluid stream 314. Data from millions of particles or cells can be collected by the flow- cytometer system 300 in a matter of minutes and displayed in a variety of formats. Illustrative example applications of flow' cytometry' include phenotyping to identify and count specific cell types within a population, analyzing DNA or RNA content within cells, determining presence of antigens on a surface or within cells, and assessing cell health status.

[0041] As shown in the illustrative example of FIG. 4, the flow' cytometer system 300 generally includes three main component subsystems: a fluidic system 310, an optical system 320, and an electronic system 330. The fluidic system 110 includes a nozzle 312 which receives a sample containing particles or cells suspended in a fluid. The nozzle 312 creates and ejects a fluid stream 314 of the particles or cells arranged in a single file line. Each particle or cell passes through one or more beams of light produced by a light source 302. The point at which a particle or cell intersects with a light beam is known as an interrogation zone 316. In some examples, the light source 302 includes one or more lasers.

[0042] The optical system 320 includes the light source 302, optical elements 322, and detectors 324. At the interrogation zone 316. light from the light source 302 hits a particle or cell in the fluid stream 314 and scatters. The optical elements 322 direct the scattered light toward the detectors 324. The detectors 324 can include a forward scatter(FSC) detector to measure scatter in the path of the light source 302, a side scatter (SSC) detector to measure scatter at a ninety-degree angle relative to the light source 302, and one or more fluorescence detectors (FL1, FL2, FL3 ... FLn) to measure the emitted fluorescence intensity at different wavelengths of light.

[0043] Generally, FSC intensity' is proportional to the size or diameter of a particle due to light diffraction around the particle. FSC may therefore be used for the discrimination of particles by size. SSC, on the other hand, is produced from light refracted or reflected by internal structures of the particle and may therefore provide information about the internal complexity or granularity' of the particle. By adding fluorescent labelling to a sample, different fluorescent signals / channels (e.g., green, orange, and red) can be analyzed for functional characteristics of a cell. For example, since T-cells present CD3 binding sites, a sample containing T-cells may be ’‘stained” with anti-CD3 antibodies conjugated with a fluorescent molecule. As these cells pass through the interrogation zone 316, the light from the light source 302 excites the fluorescent tag, or fluorochrome, to emit photons at a wavelength detectable by a fluorescence detector 324. The detectors 324 may therefore simultaneously measure several parameters and enable categorization of particles by their function based on detected wavelengths of light.

[0044] The electronic system 330 includes a waveform acquisition device 340 and a waveform analysis device 350. The waveform acquisition device 340 is communicatively coupled with the detectors 324 to receive analog waveform data 326 generated by the detectors 324. The waveform acquisition device 340 includes an analog- to-digital converter (ADC) 342 configured to digitize the waveform data and generate one or more waveforms.

[0045] The waveform analysis device 350 is configured to receive the digital waveform data and display it for a user of the flow cytometer system 300. In some embodiments, the waveform analysis device 350 comprises a computing device communicatively coupled with a flow cytometer 301. such as over a network. The flow cytometer 301 may include the fluidic system 310, optical system 320. and waveform acquisition device 340. In other embodiments, the waveform analysis device 350 is integrated with the flow' cytometer 301.

[0046] As described above, current flow cytometers abort events that are detected by the detectors 324 for various reasons, including if cells clump together and are too large to pass through the fluidic system 110 of the flow cytometer 301, if there are airbubbles within a sample or within the fluidic system 110 that disrupt flow, if the sample is contaminated and contains debris, if a signal measured from an event is too weak, or if a sample is too concentrated with cells such that multiple cells pass through the light source 302 at the same time. Traditionally, these events are aborted to ensure the data collected is of the highest quality: however, aborted events lead to data loss, so the abort rate must be optimized to ensure valuable information is not lost. It is desirable to reduce the abort rate below a threshold value (e.g., zero percent) to mitigate data loss while analyzing the data after its collection to filter out low-quality events. The abort rate (i.e., a value between 0-1) is calculated by dividing the number of events aborted by the total number of events detected. This value can be multiplied by one hundred to calculate a percentage (i.e., a value between 0-100).

[0047] Furthermore, current flow cytometers use a field-programmable gate array (FPGA) in the waveform acquisition device 340 to obtain information about individual particles passing through the light beam. The waveform acquisition device 340 uses a single threshold value to determine when the output of the detectors 324 begins conversion from analog to digital. Only a single threshold value can be used for a single run of a sample through the flow cytometer 301. The threshold value is a constant value and may be referred to as a voltage threshold value. As such, if or when a detector 324 outputs a voltage value that crosses the threshold, digitization begins, and the digital value is sent to the FPGA. As waveform data is digitized, the FPGA computes the height, width, and area of each pulse. Besides the height, width, and area of each pulse, other data relating to the waveform, including data not exceeding the voltage threshold value, is not captured, stored, or otherwise available for analysis. If a user wishes to adjust the threshold value, the experiment has to be re-run with the new threshold value, incurring costs in resources and time.[004S] To address the above issues, the example shown in FIG. 4 illustrates a whole blood cell identifier 354 included as a component of the waveform analysis device 150. The whole blood cell identifier 354 allows a user to analyze entire waveforms (i.e., graphical representations of signals generated by cells as they pass through the light source 302 and interact with the detectors 324 within the flow cytometry system 300) and distinguish between different cell types. Furthermore, the whole blood cell identifier 354 allows a user to distinguish between cell types and low-quality data that would otherwise be aborted during a data collection phase. Thus, the whole blood cell identifier 354 identifies events within a whole blood sample that pertain to a desired cell type whiledistinguishing these events from other events that pertain to other cells found in whole blood or low-quality events. In certain examples, the whole blood cell identifier 354 “gates’’ samples by automatically selecting, or manually allowing a user to select, specific cell populations of interest that appear on an outputted region on a two- dimensional plot (e.g., a scatter plot or histogram). This focuses the analysis on a cell, or constituent, of interest within the whole blood sample while excluding unwanted background noise, debris, or constituents of the whole blood sample that are not of interest.

[0049] Furthermore, the flow cytometer system 300 is improved with a graphics processing unit (GPU) 352. In the example illustrated in FIG. 1, the GPU 352 is shown included as a component of the waveform analysis device 350. The GPU 352 processes a continuous digital stream generated by the waveform acquisition device 340. The digital stream is continuous in that the waveform acquisition device 340 does not threshold the waveform data produced by the detectors 324. In contrast to current flow cytometry techniques, during an experiment, the waveform acquisition device 340 continuously digitizes the analog waveform data 326 at a high rate (e.g., 1 GHz) without thresholding. In some instances, the GPU 352 enables removal of the FPGA from the waveform acquisition device 340.

[0050] Given the foregoing description, the waveform analysis device 350 receives a digitized version of the waveform data with increased data points, and the waveform data for an experiment is displayed and available in its entirety for processing by the GPU 352. In addition to having the capability7of processing a large stream or file of waveform data, the GPU 352 enables thresholding the waveform at the post-processing step as opposed to the waveform acquisition step. This in turn provides several technical benefits including the ability to dynamically adjust thresholds and update graphical plots in real-time without re-running an experiment. The GPU 352 may also measure and extract biologically relevant information present in the waveform data beyond the three parameters of height, width, and area. Further details of operation and advantages are discussed below.

[0051] The flow cytometer system 300 includes elements which are shown and described for purposes of discussion, and it will be appreciated that numerous variations in components and functions are possible. The optical elements 322 may include a series of filters, dichroic mirrors, and / or beam splitters to select out different wavelengths of light and provide the wavelength to the appropriate detector. The detectors 324 maycomprise, for example, photomultiplier tubes (PMTs) or avalanche photodiodes (APDs) or single photon counting devices.

[0052] FIG. 5 schematically illustrates an example of a waveform analysis device 350 of the flow cytometer system 300 of FIG. 4. The waveform analysis device 350 receives, stores, and displays waveform data that has been continuously sampled without having been thresholded upstream at the waveform acquisition device 340. The waveform analysis device 350 includes an interface 410 to receive digitized raw waveform data 432, a persistent storage 430 to store the digitized raw waveform data 432, and can include a graphical user interface (GUI) 420 to display the digitized raw7waveform data 432. The persistent storage 430 may comprise system memory such as random-access memory (RAM) and / or long-term non-volatile memory such as a hard drive.

[0053] The waveform analysis device 350 may further include the whole blood cell identifier 354 comprising a softw are application or a set of related software applications configured to instruct the GPU 352 to process the digitized raw waveform data 432. The whole blood cell identifier 354 may execute on one or more processors to provide the functionality described herein in conjunction with the GPU 352 such as receiving user input via the GUI 420. The whole blood cell identifier 354 may include one or more artificial intelligence models 402, such as a machine learning algorithm, to analyze data received from the waveform acquisition device 340. One or more components of the waveform analysis device 350 may reside in a cloud computing application in a netw ork distributed system. In that regard, the waveform analysis device 350 may be any of a variety of computing devices, including, but not limited to, a personal computing device, a server computing device, or a distributed computing device.

[0054] FIG. 6 illustrates a method 500 of preparing a sample to be analyzed using a flow cytometer that includes lysing and washing the sample.

[0055] The method 500 includes a first step of receiving a sample 502. Generally, the sample is a whole blood sample drawn from a patient. As one example, a laboratory providing flow cytometry services receives a whole blood sample to be prepared for a leukemia or lymphoma panel. Constituents of blood include plasma, red blood cells, white blood cells, and platelets. Leukemia or lymphoma affects white blood cells (e.g., cause abnormally high w hite blood cell counts), and therefore subsets of the white blood cells are the constituent of the blood that is targeted for analysis in the leukemia or lymphoma panel.

[0056] The method 500 includes a step of receiving a panel selection 504. The panel selection includes a combination of labeling reagents (e.g., fluorochrome-labeled antibodies) that target and label one or more desired constituents within the whole blood sample (e.g., white blood cells). The panel selection may be made based on a variety of considerations. In certain non-limiting examples, these considerations include the research objectives of the user, the constituent of interest within the whole blood sample, the number of fluorescence channels available on the flow cytometer, and the compatibility of the labeling reagent with the sensors on the flow cytometer.

[0057] The method 500 includes adding one or more labeling reagents 506. The one or more labeling reagents are added to the whole blood sample based on the panel selection that is made by a user. In certain examples, the labeling reagent is used to stain the blood and includes an antibody reagent that attaches to white blood cells. In certain examples, the antibody reagent can include a fluorescent dye, for example, which allows for analysis of the white blood cells by flow cytometry. In some examples, cell washing is performed on the blood prior to adding the antibody reagent in order to remove the plasma and associated proteins that interfere with staining (e.g., such that primarily red blood cells and white blood cells remain).

[0058] The method 500 includes lysing undesired cellular constituents within the sample 508. In certain examples where a leukemia or lymphoma panel is prepared, red blood cells may be lysed to increase the ratio of white blood cells to red blood cells within the sample. This, in turn, aids in the isolation of white blood cells within a whole blood sample and limits the abort rate in flow cytometry' measurements.

[0059] The method 500 includes washing the lysed sample volume 510. The purpose of a wash step is to create a homogenous sample that contains the constituent(s) of interest (e.g., white blood cells) by removing the cellular debris of the lysed cells, eliminating unlysed cells, and removing the lysis reagent(s) added in step 508.

[0060] It is desirable to produce a sample that includes one or more desired constituents that are not affected by the lysing and washing steps. Washing the sample after adding a lytic agent does not guarantee the white blood cells will be suitable for analysis, as the lytic agent may affect the integrity of the desired constituents and negatively impact the results of future experiments.

[0061] The method 500 includes generating flow cytometry' data 512. Flow cytometry data is generated by running the sample through the flow cytometry system300. The flow cytometry system 300 senses cells, creates data and transmits the data to the waveform analysis device 350 for further analysis.

[0062] FIG. 7 illustrates a method 600 of preparing a sample for analysis that is a simplified version of the method 500 of FIG. 6 and does not include a step to lyse undesired constituents within the sample 508 or wash the lysed sample volume 510. As discussed above, it is desirable to remove the lysing / washing steps 508, 510 to avoid damaging the integrity of constituent(s) of interest within the whole blood sample. Furthermore, the method does not include a dilution step that can lower the concentration of white blood cells within a whole blood solution to levels that are not suitable for analysis.

[0063] The method 600 includes receiving a whole blood sample 602, receiving a panel selection 604 (e.g., a selection of labeling reagents designed to label white blood cells), add at least one labeling reagent that corresponds to the panel selection 606, and generate flow7cytometry data 608 by analyzing the whole blood sample within a flow cytometer. Furthermore, the flow cytometry data is analyzed using the waveform analysis device 350 as illustrated and described above with reference to FIGS. 4-5 and illustrated and described below with reference to FIGS. 8-10.

[0064] FIG. 8 illustrates a method 700 of analyzing a whole blood sample using the waveform analysis device of FIGS. 4-5. The method 700 includes steps that can be used to analyze the flow cytometry data 610 as illustrated and described above with respect to FIG 7.

[0065] The method 700 includes a step of receiving flow cytometry7data 702. The flow cytometry7data includes waveform data, which displays events that are detected by the flow cytometry system 300. After the events are detected, flow cytometry data is generated by the flow cytometry system 300. Specifically, the flow' cytometry system 300 includes the w aveform acquisition device 340 that is communicatively coupled with the detectors 324 to receive analog waveform data 326 generated by the detectors 324. The waveform acquisition device 340 includes an analog-to-digital converter (ADC) 342 configured to digitize the waveform data and transmit the waveform data to the waveform analysis device 350. The waveform analysis device 350 is configured to receive the digital w aveform data and display it for a user of the flow7cytometer system 300.

[0066] The method 700 includes a step of identifying at least one constituent of interest 704. The at least one constituent of interest may be identified by the waveform analysis device 350 or a user based on the panel selection that was made prior to datacollection and the objectives of the research. In certain examples as described above, the at least one constituent of interest is white blood cells within a whole blood sample.

[0067] The method 700 includes a step of isolating the constituent(s) of interest 706. Step 706 includes isolating at least one event pertaining to the constituent(s) of interest by identifying when the flow cytometry data indicates at least one event includes the characteristics that pertain to the at least one constituent of interest. In certain examples, and as illustrated and described below in further detail with respect to FIGS. 9-10, the at least one event is identified by comparing flow cytometry channels that include measurements of various characteristics of the event. In certain examples, the flow cytometry channels include data pertaining to the forward scatter, side scatter, and intensity of one or more labeling reagents used to label specific the constituent(s) of interest within the whole blood sample. In certain examples, after the constituent(s) of interest are isolated, one or more other constituents are ‘'gated out” (i.e., the data is displayed on a scatter plot or histogram and cell populations are selected within a region of the graph that pertain to the constituents of interest without highlighting the other constituents) without eliminating any data. In certain examples, the constituents of interest are isolated from the other constituents by identifying unique characteristics of the constituent of interest and identifying events that include those unique characteristics. In a non-limiting example, and as illustrated and described in FIGS. 9-11, the intensity of a fluorescence of a fluorochrome-labeled antibody that uniquely targets the constituent of interest (e.g., a white blood cell) may be measured, and the constituent of interest may be isolated from other constituents because they uniquely exhibit this fluorescence. This allows a user to analyze the constituents of interest independently from the other constituents.

[0068] The method 700 includes a step of analyzing the constituent(s) of interest 708. The constituent(s) of interest can be analyzed for a variety of reasons. In one example, a patient wishes to be tested for leukemia or lymphoma. A whole blood sample is prepared and analyzed with white blood cells labeled and any other constituents (e.g., red blood cells) gated out to isolate the white blood cells within the flow cytometry data. The white blood cells can then be analyzed to perform clinical diagnostics of diseases and conditions related to the immune system, such as abnormalities in white cell populations that may indicate an infection, an autoimmune disease, or other white blood cell malignancies.

[0069] FIG. 9 illustrates sample waveforms generated by the flow cytometry system of FIG. 4, including events that generated a forward scatter, a side scatter, and / or a fluorescence of a fluorochrome-labeled antibody.

[0070] The sample waveforms are illustrated on a two-dimensional plot 800 measuring the intensity of light detected by a plurality7of sensors within the flow cytometry system 300 (measured on the y-axis 802) over time (measured on the x-axis 804). The waveforms include a plurality of events 806. The events 806 occur on the two- dimensional plot 800 where at least one peak (e.g., peaks 812, 822, 832) is viewed in the intensity7of the signals of one or more channels. In this example, the one or more channels include three different channels 810, 820, 830. A first channel 810 includes fluorescent channel data pertaining to the intensity of light emitted from fluorochrome-labeled antibodies used to identify the constituent of interest (e.g., at least one CD45 monoclonal antibody labeled with a fluorochrome such as FITC). The second channel 820 includes side scatter data pertaining to the intensity7of one or more side scatters that is detected by a side scatter detector within the flow cytometry system 300. The third channel 830 includes forward scatter data pertaining to the intensity of one or more forward scatters that is detected by a forward scatter detector within the flow cytometry system 300. The event 806 includes peak intensities 812, 822, 832 in each of the first channel 810, the second channel 820, and third channel 830 indicating a signal was measured by the side scatter detector, the forward scatter detector, and a detector used to measure the intensity of light emitted from the fluorochrome labeled antibody.

[0071] In this example, the event 806 that includes peaks in each of the first channel 810, the second channel 820, and the third channel 830 is indicative of a white blood cell because an event was detected that created a peak in each channel (i.e.. the event scattered light in the forward and side directions while also fluorescing the fluorochrome-labeled antibody^ that specifically targets white blood cells). Each of the other events (i.e., each event that is not labeled 812, 822, and 832) indicate other constituents are present within the whole blood sample because they do not contain peaks in each of the three channels 810, 820, 830. In certain examples, the other constituent that is detected is a red blood cell. In certain examples, the whole blood cell identifier can compare additional characteristics of the events to determine which events are a constituent of interest, including a time duration for the whole blood constituents to pass through a light source within a flow cytometry system.

[0072] In certain examples, a flow cytometry panel selection can include any number of channels may be used to include any number of characteristics of events that are detected by the flow cytometer system 300. Furthermore, the channels may include any characteristic that is measurable by a flow cytometer. For example, any number of channels may be used to detect any number of fluorescent characteristics of cells. In a non-limiting example, a flow cytometer may measure two or more fluorescent labels with two or more channels, where T-cells present with CD3. CD45. or any other antibody binding site may be stained with anti CD3 / CD45 antibodies conjugated with a fluorescent molecule.

[0073] FIG. 10 illustrates a sample event that is indicative of a white blood cell. The sample waveforms are illustrated on a two-dimensional plot 900 that is substantially similar to FIG. 9, but the two-dimensional plot 900 includes a magnification on the second peak 822 and the third peak 832. In certain examples, the intensity the of peak 832 in the third channel 830 may be less than the intensity of a peak 822 in the second channel 820 or a peak 812 in the first channel 810.

[0074] FIG. 1 1 illustrates example graphs that show the desired constituents being isolated from the other constituents within a whole blood sample.

[0075] A first graph 1000 displays the total number of events 1006 measured from a whole blood sample when data is collected using the flow cytometry system 300. The first graph 1000 plots the events 1006 based on the intensity of the forward scatter detected by the forw ard scatter detector (on the x-axis 1004) versus the intensity of the side scatter detected by the side scatter detector (on the y-axis 1002). It is difficult to discern which events pertain to a constituent of interest, such as white blood cells, because the constituent of interest includes similar characteristics as the other constituents. Furthermore, in whole blood samples where the constituent of interest is a white blood cell, it is especially difficult to isolate the white blood cells because the red blood cells far outnumber the white blood cells within the whole blood sample. Thus, it is desirable to determine unique characteristics of the white blood cells that can be used to isolate them from the red blood cells.

[0076] The second graph 1010 includes the total number of events measured from a whole blood sample; however, the events are separated into constituents of interest 1018 and other constituents 1016 based on the fluorescence of a fluorochrome-labeled antibody that uniquely binds to the constituents of interest 1018 (i.e.. the white blood cells) and not the other constituents (i.e., the red blood cells). The intensity of thefluorescence of the fluorochrome-labeled antibody is measured on the x-axis 1014 and the intensity of the side scatter measured by a side scatter detector is measured on the y- axis 1012. The whole blood cell identifier 354 is configured to analyze whole blood samples in one or more dimensions and isolate the constituent(s) of interest 1018 by considering any number of characteristics of the constituent of interest 1018 that differentiate the constituent of interest 1018 from the other constituents 1016. Once the constituent of interest 1018 is isolated from the other constituents 1016, it can be analyzed independently from the other constituents 101 . In certain examples, the constituent of interest 1018 is analyzed independently from the other constituents 1016 without deleting data pertaining to the other constituents 1016. In certain examples, the whole blood cell identifier 354 is configured to analyze the whole blood samples in one or more dimensions in real time without having to recollect data.

[0077] FIG. 12 illustrates an example method 1200 of analyzing flow cytometry data that was collected without aborting any events. The step of preparing a whole blood specimen 1202 is substantially similar to steps 602, 604, and 606 of FIG. 7, where a whole blood sample is taken from a patient, a panel selection is made, and a labeling reagent is added to the sample based on the panel selection that was made.

[0078] The example method 1200 includes a step 1204 of generating flow cytometry data without aborting any events 1204. As described above, in traditional flow cytometry, events that are detected can be aborted for several reasons to remove low-quality events and preserve the quality of the flow cytometry data. However, one disadvantage to aborting events is that it is possible to abort an event pertaining to a constituent of interest, which would negatively manipulate the results of an experiment. For example, white blood cell count is an important factor in diagnosing cancers such as leukemia. If a clinician is diagnosing a patient with leukemia, and many events pertaining to white blood cells are removed, then a whole blood test may falsely indicate the patient does not have an elevated white blood cell count. This, in turn, may influence a clinician to improperly diagnose the patient. This is especially applicable to whole blood samples that do not include steps to lyse cells or dilute the sample, as these samples often have significantly higher abort rates than samples that include one or more steps to lyse cells or dilute the sample.

[0079] Thus, it is desirable to capture as many events as possible by generating flow cytometry data without aborting any events. The whole blood cell identifier 354 analyzes each event based on the characteristics of the event (e.g., the forward scatter, side scatter,and / or fluorescence of a fluorochrome-labeled antibody) and distinguishes the constituents of interest from the other constituents, where the other constituents also include events that would be aborted in a traditional flow cytometry system.

[0080] The method 1200 includes steps to analyze the flow cytometry data 1206 and prepare an output 1208 after the flow cytometry data is collected without aborting any events 1204. This process is similar to the steps described in FIGS. 8-11, but the steps include analyzing a complete set of events that include the constituents of interest, and all other constituents (i.e., any other cells within the whole blood sample and any events that would be aborted by a traditional flow cytometer).

[0081] FIG. 13 shows an exemplary' architecture of a computing device that can be used to implement aspects of the present disclosure, illustrates an exemplary architecture of a computing device 1300 that can be used to implement aspects of the present disclosure, including the aspects of the waveform acquisition device 140 and the waveform analysis device 150, as described above. The computing device 1300 illustrated in FIG. 14 can be used to execute the operating system, application programs, and software modules (including the software engines) described herein.

[0082] The computing device 1300 includes at least one processing device 1302, such as a central processing unit (CPU). In this example, the computing device 1300 also includes a system memory 1304, and a system bus 1306 that couples various system components including the system memory 1304 to the at least one processing device 1302. The system bus 1306 is one of any number of types of bus structures including a memory bus, or memory' controller; a peripheral bus; and a local bus using any of a variety of bus architectures.

[0083] The system memory 1304 includes read only memory (ROM) 1308 and random-access memory (RAM) 1310. A basic input / output system 1312 containing the basic routines that act to transfer information within computing device 1300, such as during start up, is ty pically stored in the read only memory' 1308. In some examples, the system memory 1304 has a large memory capacity, such as equal to or greater than one Terabyte of RAM. The RAM can be used to load and subsequently analyze the waveform data (e.g., the raw waveform data, such as stored in a raw waveform data file, which can include digitalized waveform data).

[0084] The computing device 1300 also includes a secondary storage device 1314 in some embodiments, such as a hard disk drive, for storing digital data. The secondary storage device 1314 is connected to the system bus 1306 by a secondary storage interface1316. In some examples, the secondary' storage devices 1314 and their associated computer readable media provide nonvolatile storage of computer readable instructions (including application programs and program modules), data structures, and other data for the computing device 1300.

[0085] Although the exemplary environment described herein employs a hard disk drive as a secondary storage device, other types of computer readable storage media are used in other embodiments. Examples of these other types of computer readable storage media include magnetic cassettes, flash memory' cards, digital video disks, Bernoulli cartridges, compact disc read only memories, digital versatile disk read only memories, random access memories, or read only memories. Some embodiments include non- transitory media. Additionally, such computer readable storage media can include local storage or cloud-based storage.

[0086] Several program modules can be stored in secondary storage device 1314 or the system memory' 1304, including an operating system 1318, one or more application programs 1320, other program modules 1322 (e.g., software engines described herein), and program data 1324. The computing device 1300 can utilize any suitable operating system, such as Microsoft Windows™, Google Chrome™, Apple OS, and any other operating system suitable for a computing device.

[0087] In some examples, a user provides inputs to the computing device 1300 through one or more input devices 1326. Examples of input devices 1326 include a keyboard 1328, mouse 1330, microphone 1332, and touch sensor 1334 (such as a touchpad or touch sensitive display). Additional examples include additional types of input devices 1326, or fewer types of input devices 1326. The input devices 1326 are connected to the at least one processing device 1302 through an input / output interface 1336 coupled to the system bus 1306. The input / output interface 1336 can include any number of input / output interfaces, such as a parallel port, serial port, game port, or a universal serial bus. Wireless coupling between input devices 1326 and the input / output interface 1336 is possible as well, such as through infrared, BLUETOOTH®, 802.11a / b / g / n. cellular, or other radio frequency communication systems in some possible embodiments.

[0088] In this example embodiment, a display device 1342, such as a monitor, liquid crystal display device, projector, or touch sensitive display device, is also connected to the system bus 1306 via a video adapter 1340. In addition to the display device 1342. thecomputing device 1300 can include various other peripheral devices (not shown), such as speakers or a printer.

[0089] When used in a local area networking environment or a wide area networking environment (such as the Internet), the computing device 1300 is typically connected to a network such as through a network interface 1338, such as an Ethernet interface. Other possible embodiments use other communication devices. For example, some embodiments of the computing device 1300 include a modem for communicating across the network.

[0090] The computing device 1300 typically includes at least some form of computer readable media. Computer readable media includes any available media that can be accessed by the computing device 1300. By way of example, computer readable media include computer readable storage media and computer readable communication media.

[0091] Computer readable storage media includes volatile and nonvolatile, removable, and non-removable media implemented in any device configured to store information such as computer readable instructions, data structures, program modules or other data. Computer readable storage media includes, but is not limited to, random access memory, read only memory7, electrically erasable programmable read only memory, flash memory, compact disc read only memory, digital versatile disks or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by the computing device. Computer readable storage media does not include computer readable communication media.

[0092] Computer readable communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery7media. The term “modulated data signal” refers to a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, computer readable communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency, infrared, and other wireless media. Combinations of any of the above are also included within the scope of computer readable media.

[0093] The computing device 1300 illustrated in FIG. 13 is also an example of programmable electronics, which may include one or more such computing devices, andwhen multiple computing devices are included, such computing devices can be coupled together with a suitable data communication network to collectively perform the various aspects disclosed herein.

[0094] The above description is illustrative and is not restrictive. Many variations of the invention will become apparent to those skilled in the art upon review of the disclosure. The scope of the invention should, therefore, be determined not with reference to the above description, but instead should be determined with reference to the pending claims along with their full scope or equivalents.

[0095] Additional examples are described in the following clauses, which are consistent with the present disclosure. The clauses may further be combined with any one or more of the features or embodiments disclosed herein.

[0096] Clause 1. A method for analyzing particles within a flow cytometry system, the method comprising: receiving a whole blood sample; receiving a panel selection corresponding to one or more constituents within the whole blood sample, wherein the one or more constituents include one or more desired constituents; adding at least one labeling reagent to the whole blood sample, the at least one labeling reagent being configured to label the one or more desired constituents; collecting flow cytometry data from the whole blood sample; and analyzing the one or more constituents by: generating one or more waveforms, the one or more waveforms including events that correspond to the one or more desired constituents within the whole blood sample; and analyzing the one or more waveforms to identify the events that correspond to white blood cells.

[0097] Clause 2. The method of clause 1, further comprising transmitting the flow cytometry data to an electronic system, wherein the electronic system includes a waveform acquisition device and a waveform analysis device.

[0098] Clause 3. The method of clause 2, wherein the one or more waveforms are generated using the waveform acquisition device and the one or more constituents are analyzed using the waveform analysis device.

[0099] Clause 4. The method of any one of clauses 1-3, wherein the at least one labeling reagent is added to the whole blood sample without adding a lytic agent, diluting the whole blood sample, or washing the whole blood sample.

[0100] Clause 5. The method of any one of clauses 1-4, wherein the panel selection includes fluorochrome-labeled antibodies.

[0101] Clause 6. The method of clause 5, wherein the panel selection includes fluorescein isothiocyanate.

[0102] Clause 7. The method of clause 6, wherein the fluorescein isothiocyanate is used to label at least one monoclonal antibody, wherein the at least one monoclonal antibody includes at least one CD45 monoclonal antibody.

[0103] Clause 8. The method of any one of clauses 1-7, wherein the flow cytometry system includes: a light source for generating a light beam toward an interrogation zone; and an optical system including detectors for detecting radiated light from the one or more constituents passing through the light beam in the interrogation zone.

[0104] Clause 9. The method of clause 8, wherein the flow cytometry data is generated by using the light source and the optical system to detect the one or more constituents that pass through the interrogation zone.

[0105] Clause 10. A method for analyzing flow cytometry data, the method comprising: receiving flow cytometry data, wherein the flow cytometry data includes one or more waveforms that are representative of characteristics of whole blood constituents within a whole blood sample, the whole blood constituents include at least one constituent of interest and at least one other constituent; identifying the at least one constituent of interest; isolating at least one event pertaining to the at least one constituent of interest by identifying at least one event that includes the characteristics that indicate the at least one constituent of interest was detected; and analyzing the at least one constituent of interest independently from the at least one other constituent.

[0106] Clause 11. The method of clause 10. wherein the one or more waveforms include one or more of side scatter data, forward scatter data, and fluorescent channel data, or a time duration for the whole blood constituents to pass through a light source within a flow cytometry system.

[0107] Clause 12. The method of clause 11. wherein the fluorescent channel data includes fluorochrome-labeled antibodies.

[0108] Clause 13. The method of clause 12, wherein the fluorochrome-labeled antibodies include a CD45 fluorochrome-labeled antibody.

[0109] Clause 14. The method of clause 13, wherein the at least one constituent of interest is identified by isolating the at least one event within the flow cytometry data that includes peak intensities in the side scatter data, the forward scatter data, and the fluorescent channel data, wherein the fluorescent channel data includes the CD45 fluorochrome-labeled antibody.

[0110] Clause 15. The method of any one of clauses 10-14, wherein the at least one constituent of interest includes one or more white blood cells.[OHl] Clause 16. The method of any one of clauses 10-15, wherein the at least one other constituent includes one or more red blood cells.

[0112] Clause 17. The method of any one of clauses 10-16, wherein the at least one constituent of interest is analyzed independently from the at least one other constituent without removing data pertaining to the at least one other constituent.

[0113] Clause 18. The method of any one of clauses 10-17, wherein the at least one constituent of interest is analyzed independently from the at least one other constituent without deleting data pertaining to the at least one other constituent.

[0114] Clause 19. A flow cytometry7system for analyzing particles, the flow cytometry system comprising: at least one processing device: and a non-transitory computer readable storage media storing instructions which, when executed by the at least one processing device, cause the at least one processing device to: receive flow cytometry data, wherein the flow cytometry data includes one or more dimensions to quantify characteristics of whole blood constituents within a whole blood sample, the whole blood constituents include at least one constituent of interest and at least one other constituent; identify the at least one constituent of interest; isolate at least one event pertaining to the at least one constituent of interest by identifying when the flow cy tomctry data indicates at least one event includes the characteristics that pertain to the at least one constituent of interest; and analyze the at least one constituent of interest independently from the at least one other constituent, wherein the at least one constituent of interest and the at least one other constituent are analyzed without aborting any events.

[0115] Clause 20. A method for analyzing particles within a flow7cytometry system, the method comprising: receiving a whole blood sample; receiving a panel selection corresponding to one or more constituents within the whole blood sample, wherein the one or more constituents include one or more desired constituents; adding at least one labeling reagent to the whole blood sample, the at least one labeling reagent being configured to label the one or more desired constituents; collecting flow cytometry data from the whole blood sample; and analyzing the one or more constituents, wherein the one or more constituents are analyzed without aborting any events.

[0116] One or more features from any embodiment may be combined with one or more features of any other embodiment without departing from the scope of the invention.

Claims

WHAT IS CLAIMED IS:

1. A method for analyzing particles within a flow cytometry system, the method comprising: receiving a whole blood sample; receiving a panel selection corresponding to one or more constituents within the whole blood sample, wherein the one or more constituents include one or more desired constituents; adding at least one labeling reagent to the whole blood sample, the at least one labeling reagent being configured to label the one or more desired constituents; collecting flow cytometry data from the whole blood sample; and analyzing the one or more constituents by: generating one or more waveforms, the one or more waveforms including events that correspond to the one or more desired constituents within the whole blood sample; and analyzing the one or more waveforms to identify the events that correspond to white blood cells.

2. The method of claim 1, further comprising transmitting the flow cytometry' data to an electronic system, wherein the electronic system includes a waveform acquisition device and a waveform analysis device.

3. The method of claim 2, wherein the one or more waveforms are generated using the waveform acquisition device and the one or more constituents are analyzed using the waveform analysis device.

4. The method of any' one of claims 1-3, wherein the at least one labeling reagent is added to the whole blood sample without adding a lytic agent, diluting the whole blood sample, or washing the whole blood sample.

5. The method of any' one of claims 1-4, wherein the panel selection includes fluorochrome-labeled antibodies.

6. The method of claim 5, wherein the panel selection includes fluorescein isothiocyanate.

7. The method of claim 6, wherein the fluorescein isothiocyanate is used to label at least one monoclonal antibody, wherein the at least one monoclonal antibody includes at least one CD45 monoclonal antibody.

8. The method of any one of claims 1-7, wherein the flow cytometry system includes: a light source for generating a light beam toward an interrogation zone; and an optical system including detectors for detecting radiated light from the one or more constituents passing through the light beam in the interrogation zone.

9. The method of claim 8, wherein the flow cytometry data is generated by using the light source and the optical system to detect the one or more constituents that pass through the interrogation zone.

10. A method for analyzing flow cytometry data, the method comprising: receiving flow cytometry data, wherein the flow cytometry data includes one or more waveforms that are representative of characteristics of whole blood constituents within a whole blood sample, the whole blood constituents include at least one constituent of interest and at least one other constituent; identifying the at least one constituent of interest; isolating at least one event pertaining to the at least one constituent of interest by identifying at least one event that includes the characteristics that indicate the at least one constituent of interest was detected; and analyzing the at least one constituent of interest independently from the at least one other constituent.

11. The method of claim 10, wherein the one or more waveforms include one or more of side scatter data, forward scatter data, and fluorescent channel data, or a time duration for the whole blood constituents to pass through a light source within a flow cytometry system.

12. The method of claim 11. wherein the fluorescent channel data includes fluorochrome-labeled antibodies.

13. The method of claim 12. wherein the fluorochrome-labeled antibodies include a CD45 fluorochrome-labeled antibody.

14. The method of claim 13, wherein the at least one constituent of interest is identified by isolating the at least one event within the flow cytometry data that includes peak intensities in the side scatter data, the forward scatter data, and the fluorescent channel data, wherein the fluorescent channel data includes the CD45 fluorochrome-labeled antibody.

15. The method of any one of claims 10-14. wherein the at least one constituent of interest includes one or more white blood cells.

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